CHAMPAIGN, Ill. -- To better protect human health, the role of uncertainty must be considered in cleaning up contaminated groundwater sites, researchers at the University of Illinois say. They are developing a risk-management model that provides a framework for identifying promising candidate designs while improving understanding of the critical factors involved in risk-based remediation.
"Many states now allow site-specific, risk-based criteria to be used in lieu of fixed drinking-water standards," said Barbara Minsker, a UI professor of civil and environmental engineering. The criteria, she noted, are usually developed by negotiating an acceptable risk level with regulators and then calculating a corresponding contaminant-concentration target under conservative assumptions.
"As we move toward using risk as the criteria for how we clean up contaminated sites, it is very important that we consider uncertainty," Minsker said. "By evaluating tradeoffs among cost and risk under conditions of uncertainty, our model will help decision makers make better decisions."
Minsker's risk-management model combines a genetic algorithm with a fate and transport simulation model and a risk assessment module to identify potential remediation designs. The genetic algorithm searches the decision space for remediation designs that best meet a specified management objective, such as minimizing cost and risk. The simulation model and risk-assessment module are used to predict the risk associated with candidate remediation designs.
To illustrate the importance of considering uncertainty and cost in risk-based remediation design, Minsker and her former students J. Bryan Smalley and Beth Padera applied the model to a small case study based on the Borden aquifer in Canada.
"The model identified a number of remediation designs, each of which entailed a different tradeoff between cost and risk," Minsker said. "While there was a range of risk levels that could be achieved with little increase in cost, beyond a certain level the costs increased substantially. When uncertainty was considered, the effects of uncertainty on the cost of remediation were shown to be as important as the target risk level specified."
Currently, the model can evaluate tradeoffs between cost and risk without considering uncertainty, or it can minimize cost given a specified maximum risk level under conditions of uncertainty. Ultimately, the model will allow tradeoffs among cost, risk and cleanup time to be considered under uncertainty during the remediation design process.
"With such information readily available," Minsker said, "negotiations can focus on design issues that have the most impact on the cost and effectiveness of the remediation plan."
Minsker will present the model during a symposium on scientific uncertainty and risk management at the American Chemical Society meeting, to be held Aug. 20-24 in Washington, D.C. The National Science Foundation and the U.S. Army Research Office are supporting development of the model.
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